ODSC Santa Clara Data Science

To access this webinar, please register here: https://hubs.li/Q02bNw-60

Topic: "Building Responsible and Safe Generative AI Applications"

Speaker: Mehrnoosh Sameki, Principal PM Manager, Responsible AI Tools Area Lead at Microsoft

Mehrnoosh is responsible for overseeing product initiatives that focus on responsible Artificial Intelligence and machine learning model understanding tools, such as interpretability, fairness, reliability, and decision-making, within the Open Source and Azure Machine Learning platforms.

She is co-founded several open-source repositories, including Fairlearn, Error Analysis, and Responsible-AI-Toolbox, and is also a contributor to the InterpretML offering. Mehrnoosh holds a Ph.D. in Computer Science from Boston University, where she is currently an Adjunct Assistant Professor, teaching courses on responsible AI. Prior to her role at Microsoft, she worked as a Data Scientist in the retail industry, utilizing data science and machine learning to improve customers' personalized shopping experiences.

Abstract:
As large language models (LLMs) become more widely adopted, it is crucial to understand their effective utilization, copilot development, evaluation, operationalization, and monitoring in real-world applications. This session will provide insights into incorporating responsible AI practices and safety features into your generative AI applications. You will gain knowledge on assessing your copilots and generative AI applications, mitigating content-related risks, addressing hallucinations, jailbreak, and copywrite issues, ensuring fairness, and enhancing the overall quality and safety of your copilot.

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To access this webinar, please register here: https://hubs.li/Q027CWFD0

Topic: "From Raw Data to Insights: Simplifying Data Validation and Enrichment"

Speaker#1: Emily Washington, SVP, Product Management at Precisely
Emily is responsible for driving enterprise-level product strategy and roadmaps for Precisely’s data governance, data quality, data prep and MDM capabilities. She works closely with customers and product development teams to drive development, introduction, and adoption of all new products in support of our data integrity product strategy. Emily joined Precisely via acquisition of Infogix in 2021, where she led product strategy and held leadership roles in product management, customer success and marketing.

Speaker#2: Andy Bell, VP, Product Management - Data at Precisely
Andy is Vice President of Global Data Product Management at Precisely, responsible for the global data portfolio. Andy has accumulated a wealth of experience over 25 years in data and analytics, leading teams involved in retail location analysis, product development, data science and GIS. He has previously worked for GlaxoSmithKline, BellHanson, GMAP and CallCredit instigating a number of innovative data developments as well as new ways of applying data and insight to new market problems. Andy is currently driving the data strategy at Precisely with his team of Product Managers, identifying and developing new and innovative data products to meet new and exciting client demands.

Join us to learn about:
· The importance of data validation for critical datasets like address and contact information
· Accelerating your time to insight through a simple approach to data validation and enrichment
· Streamlining data management and enrichment processes across multiple datasets to add context to your data and improve the speed and accuracy of decision-making.

ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02b5zmq0
• Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q02bC0gt0

Topic: "Predictive Maintenance: The Power of Feature Engineering for Manufacturing Data Scientists"

Speaker: Hari Narayanan, Senior Data Scientist at dotData

As a customer-facing data scientist, he works in use cases involving the automotive, healthcare, retail, and insurance industries. Before joining dotData, he worked for top-tier OEMs including General Motors and Ford. He has published patents and publications and is also a recipient of the Technical Excellence Award at Ford. Together, he brings eight years of experience in the Automotive and Software industry. He has developed solutions for use cases involving Predictive Maintenance, Content Optimization, Inventory Optimization, Machine Life Optimization, and Customer Risk Prediction. Hari has received his Master’s degree in Industrial Engineering from Clemson University, specializing in Operations Research and Advanced Statistics.

Abstract:
Explore the untapped possibilities of Predictive Maintenance! Join data scientists, engineers, and manufacturing professionals on an engaging journey through predictive maintenance use cases, shedding light on this often underexplored realm of Machine Learning.

Hear from Hari Narayanan, a key member of dotData’s Data Science team, as he delves into the power of predictive analytics, machine learning, and feature engineering in the manufacturing landscape. Uncover the challenges of predictive maintenance use cases, challenging conventional approaches, and discover the potential of alternative methodologies like feature engineering.

Key Takeaways:
- Build accurate target variables
- Creating aggregated features
- Developing interaction-based features to model complex relationships

ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02b5zmq0
• Code of conduct: https://odsc.com/code-of-conduct/